Automotive sensor integration module

ABSTRACT

An automotive sensor integration module including a plurality of sensors which differ in at least one of a sensing period or an output data format, and a signal processor, which simultaneously outputs, as sensing data, pieces of detection data respectively output from the plurality of sensors on the basis of the sensing period of any one of the plurality of sensors, calculates a reliability value of each of the pieces of detection data on the basis of the pieces of detection data and external environment data, and outputs the reliability value as reliability data.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority from and the benefit of Korean PatentApplication No. 10-2019-0133130, filed on Oct. 24, 2019, which is herebyincorporated by reference for all purposes as if set forth herein.

BACKGROUND Field

Exemplary embodiments relate to an automotive sensor integration module.

Discussion of the Background

As technology becomes more advanced, various sensors, electronicdevices, and the like are also provided in a vehicle for userconvenience. In particular, research regarding an advanced driverassistance system (ADAS) has been actively conducted for users' drivingconvenience. Furthermore, the development of autonomous vehicles isactively under way.

The ADAS and the autonomous vehicles require a large number of sensorsand electronic devices to identify objects outside a vehicle.

Referring to FIG. 1, in order to detect objects in front of a vehicle, acamera, a lidar, a radar sensor, etc. are disposed in front of thevehicle, but are disposed at different positions, respectively.

Although objects should be identified on the basis of detection resultsdetected by sensors at the same timing in order to improve performancein detecting objects, it is not easy to synchronize object detectionsensors because the sensors are disposed at different positions.Furthermore, when there is dirt or other foreign matter is disposed onouter cover surfaces of the sensors, it may become difficult for each ofthe sensors to output a detection result for normal objectdiscrimination.

The above information disclosed in this Background section is only forenhancement of understanding of the background of the invention and,therefore, it may contain information that does not constitute priorart.

SUMMARY

Exemplary embodiments of the present invention provide an automotivesensor integration module.

Exemplary embodiments of the present invention also provide anautomotive sensor integration module in which a plurality ofsynchronized sensors are arranged.

Additional features of the invention will be set forth in thedescription which follows, and in part will be apparent from thedescription, or may be learned by practice of the invention.

An exemplary embodiment of the present invention provides an automotivesensor integration module including a plurality of sensors which differin at least one of a sensing period or an output data format, and asignal processing unit, which simultaneously outputs, as sensing data,pieces of detection data respectively output from the plurality ofsensors on the basis of the sensing period of any one of the pluralityof sensors; calculates a reliability value of each of the pieces ofdetection data on the basis of the pieces of detection data and externalenvironment data; and outputs the reliability value as reliability data.

Another exemplary embodiment of the present invention provides anautomotive sensor integration module including a plurality of sensorswhich differ in at least one of a sensing period or an output dataformat, an output synchronization unit, which simultaneously outputs, assensing data, pieces of detection data respectively output from theplurality of sensors on the basis of the sensing period of any one ofthe plurality of sensors, and a data reliability determination unit,which calculates a reliability value of each of the pieces of detectiondata on the basis of the pieces of detection data and externalenvironment data, and outputs the reliability value as reliability data.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and areintended to provide further explanation of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the invention and are incorporated in and constitute apart of this specification, illustrate embodiments of the invention, andtogether with the description serve to explain the is principles of theinvention.

FIG. 1 is a diagram illustrating an outer shape of an autonomousvehicle.

FIG. 2 is an outside view of an automotive sensor integration moduleaccording to an exemplary embodiment of the present invention.

FIG. 3 is a diagram illustrating a vehicle in which automotive sensorintegration modules according to an exemplary embodiment of the presentinvention are arranged.

FIG. 4 is a diagram illustrating a configuration of a vehicle in whichan automotive sensor integration module according to an exemplaryembodiment of the present invention is arranged.

FIG. 5 is a diagram illustrating a configuration of an automotive sensorintegration module according to an exemplary embodiment of the presentinvention.

FIG. 6 is a diagram illustrating a configuration of the signalprocessing unit of FIG. 5.

FIG. 7 is a diagram illustrating a configuration of the data reliabilitydetermination unit of FIG. 6.

DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENTS

Various advantages and features of the present invention and methodsaccomplishing thereof will become apparent from the followingdescription of embodiments with reference to the accompanying drawings.However, the present invention is not be limited to the embodiments setforth herein but may be implemented in many different forms. The presentembodiments may be provided so that the disclosure of the presentinvention will be complete, and will fully convey the scope of theinvention to those skilled in the art and therefore is the presentinvention will be defined within the scope of claims. Like referencenumerals throughout the description denote like elements.

Unless defined otherwise, it is to be understood that all the terms(including technical and scientific terms) used in the specification hasthe same meaning as those that are understood by those who skilled inthe art. Further, the terms defined by the dictionary generally usedshould not be ideally or excessively formally defined unless clearlydefined specifically. It will be understood that for purposes of thisdisclosure, “at least one of X, Y, and Z” can be construed as X only, Yonly, Z only, or any combination of two or more items X, Y, and Z (e.g.,XYZ, XYY, YZ, ZZ). Unless particularly described to the contrary, theterm “comprise”, “configure”, “have”, or the like, which are describedherein, will be understood to imply the inclusion of the statedcomponents, and therefore should be construed as including othercomponents, and not the exclusion of any other elements.

When a certain element is referred to as being “on (or under)” anotherelement, the certain element may be disposed in contact with the uppersurface (or lower surface) of the other element or an interveningelement may be present between the other element and the certain elementdisposed on (or under) the other element.

Furthermore, it will be understood that when a certain element isreferred to as being “connected to” or “coupled to” another element,these elements may be directly connected or coupled to each other, butan intervening element may be “interposed” therebetween, or the elementsmay be connected or coupled to each other via another element.

As is customary in the field, some exemplary embodiments are describedand illustrated in the accompanying drawings in terms of functionalblocks, units, and/or modules. Those skilled in the art will appreciatethat these blocks, units, and/or modules are is physically implementedby electronic (or optical) circuits, such as logic circuits, discretecomponents, microprocessors, hard-wired circuits, memory elements,wiring connections, and the like, which may be formed usingsemiconductor-based fabrication techniques or other manufacturingtechnologies. In the case of the blocks, units, and/or modules beingimplemented by microprocessors or other similar hardware, they may beprogrammed and controlled using software (e.g., microcode) to performvarious functions discussed herein and may optionally be driven byfirmware and/or software. It is also contemplated that each block, unit,and/or module may be implemented by dedicated hardware, or as acombination of dedicated hardware to perform some functions and aprocessor (e.g., one or more programmed microprocessors and associatedcircuitry) to perform other functions. Also, each block, unit, and/ormodule of some exemplary embodiments may be physically separated intotwo or more interacting and discrete blocks, units, and/or moduleswithout departing from the scope of the inventive concepts. Further, theblocks, units, and/or modules of some exemplary embodiments may bephysically combined into more complex blocks, units, and/or moduleswithout departing from the scope of the inventive concepts.

FIG. 2 is an outside view of an automotive sensor integration moduleaccording to an exemplary embodiment of the present invention.

An automotive sensor integration module according to an exemplaryembodiment of the present invention may include a plurality of devicesand sensors for detecting objects outside a vehicle to acquire safetyinformation related to vehicle driving. In this case, the objects mayinclude a lane, another vehicle, a pedestrian, a two-wheeled vehicle, atraffic signal, light, a road, a structure, a speed bump, a geographicalfeature, an animal, etc.

The lane may be a driving lane, a lane next to the driving lane, or alane along is which an opposite vehicle travels. The lane may includeleft and right lines forming a lane.

Another vehicle may be a vehicle that is travelling in the vicinity of ahost vehicle. The other vehicle may be a vehicle within a predetermineddistance from the host vehicle. For example, the other vehicle may be avehicle that is located within a predetermined distance from the hostvehicle and precedes or follows the host vehicle.

The pedestrian may be a person in the vicinity of a host vehicle. Thepedestrian may be a person located within a predetermined distance fromthe host vehicle. For example, the pedestrian may be a person on asidewalk or the roadway within a predetermined distance from the hostvehicle.

The two-wheeled vehicle may be a vehicle that is located in the vicinityof a host vehicle and moves using two wheels. The two-wheeled vehiclemay be a vehicle that has two wheels and is located within apredetermined distance from the host vehicle. For example, thetwo-wheeled vehicle may include a motorcycle or a bicycle on a sidewalkor the roadway within a predetermined distance from the vehicle.

The traffic signal may include a traffic light, a traffic sign, apattern, or text drawn on a road surface.

The light may include light from a lamp in another vehicle, light from astreet lamp, or light emitted from the sun.

The road may include a road surface, a curve, and a slope such as anupward slope and a downward slope.

The structure may be an object which is located around the road andfixed onto the ground. For example, the structure may include astreetlight, a roadside tree, a building, a power pole, a traffic light,a bridge, etc.

The geographical feature may include a mountain, a hill, etc.

Meanwhile, the objects may be classified as a moving object or astationary object. For example, the moving object may conceptuallyinclude another vehicle, a two-wheeled vehicle, a pedestrian, etc.,while the stationary object may conceptually include a traffic signal, aroad, a structure, etc.

As such, it may be desirable to use various sensors and devices toaccurately identify various objects around a vehicle.

In order to accurately identify objects outside a vehicle, an automotivesensor integration module according to an exemplary embodiment of thepresent invention may include a plurality of different types of sensorsand devices. In addition, the automotive sensor integration moduleaccording to an exemplary embodiment of the present invention mayinclude at least one sensor and device of the same type.

Referring to FIGS. 2-5, the automotive sensor integration module 100according to an exemplary embodiment of the present invention mayinclude an infrared camera 12, an optical camera 11, a lidar 14, and aradar 13 as a sensor to identify an object outside a vehicle. Theautomotive sensor integration module 100 according to an exemplaryembodiment of the present invention illustrated in FIG. 2 is exemplarilyshown to include an infrared camera 12, an optical camera 11, a lidar14, and a radar 13 as a sensor in order to identify an object, but theinventive concepts are not limited thereto. In addition, the automotivesensor integration module 100 according to an exemplary embodiment ofthe present invention illustrated in FIG. 2 shows two infrared cameras12, one optical camera, two lidars 14, and one radar 13, but the numberof each sensor is suggested only for illustrative purposes and is notlimited thereto.

Referring to FIGS. 2-5, the automotive sensor integration module 100according to an exemplary embodiment of the present invention mayinclude a circuit board, an infrared camera 12, an optical camera 11, aradar 13, and a lidar 14. For example, the automotive sensor integrationmodule 100 according to an exemplary embodiment of the present inventionmay include a circuit board on which an infrared camera 12, an opticalcamera 11, a radar 13, and a lidar 14 are disposed and mounted.

The optical camera 11 designed to acquire outside images of a vehiclethrough light and recognize objects, light, and people around thevehicle may include a mono camera, a stereo camera, an around viewmonitoring (AVM) camera, and a 360-degree camera. The optical camera 11has advantages of being able to detect colors and accurately classifyobjects compared to other sensors, but has a disadvantage of beingaffected by environmental factors, such as darkness, backlight, snow,rain, fog, etc.

The radar 13 may detect an object on the basis of a time-of-flight (TOF)method or a phase-shift method through electromagnetic waves, and detectthe location of a detected object, the distance to the detected object,and the relative speed. The radar 13 has an advantage of being capableof long distance detection without being affected by environmentalfactors such as darkness, snow, rain, fog, etc., but has a disadvantageof failing to detect an object, made of an electromagneticwave-absorbing material, for example, a steel structure such as a tunnelor a guardrail, and thus, being unable to classify objects.

The lidar 14 may detect an object on the basis of a TOF method or aphase-shift method through laser light, and detect the location of adetected object, the distance to the detected object, and the relativespeed. The lidar 14 has advantages of being less affected byenvironmental factors such as darkness, snow, rain, fog, etc., efficientin long- and short-distance detection due to high resolution, andobjects are able to be simply classified, but has a disadvantage offailing to measure the speed of objects immediately.

The infrared camera 12 may acquire outside images of a vehicle throughinfrared rays. In particular, the infrared camera 12 may acquire outsideimages of the vehicle even in darkness at night. The infrared camera 12has advantages of being capable of long distance detection and beingable to distinguish living things from objects without being affected byenvironmental factors such as darkness, snow, rain, fog, etc. but has adisadvantage of being expensive.

The automotive sensor integration module 100 according to an exemplaryembodiment of the present invention is configured such that an outercover is coupled in the direction of the detection area of an opticalcamera 11, an infrared camera 12, a radar 13, and a lidar 14, that is,to the front surface of the automotive sensor integration module 100 tothereby protect the optical camera 11, the infrared camera 12, the radar13, and the lidar 14 from physical shocks.

As such, in order to accurately classify and identify external objectsaround a vehicle regardless of environmental factors, the advantages anddisadvantages of each sensor must be combined. Therefore, the automotivesensor integration module 100 according to an exemplary embodiment ofthe present invention discloses a structure in which a plurality ofdifferent sensors are all disposed and mounted on a circuit board. Inaddition, the automotive sensor integration module 100 according to anexemplary embodiment of the present invention may synchronize and outputdetection results of a plurality of sensors having different operationcycles, thereby having an advantage of classifying and identifyingobjects more accurately.

FIG. 3 is a diagram illustrating a vehicle in which automotive sensorintegration modules according to an exemplary embodiment of the presentinvention are arranged.

Referring to FIG. 3, a plurality of automotive sensor integrationmodules 100 according to an exemplary embodiment of the presentinvention may be arranged in a vehicle to detect objects outside thevehicle.

FIG. 3 exemplarily illustrates that four automotive sensor integrationmodules 100 are arranged in a vehicle, but is the inventive concepts arenot limited thereto. Furthermore, FIG. 3 exemplarily illustrates thatautomotive sensor integration modules 100 are arranged at right and leftfront sides of a vehicle to detect right and left objects in front ofthe vehicle, and automotive sensor integration modules 100 are arrangedat right and left rear sides of the vehicle to detect right and leftobjects in back of the vehicle.

FIG. 4 is a diagram illustrating a configuration of a vehicle in whichan automotive sensor integration module 100 according to an exemplaryembodiment of the present invention is arranged.

The vehicle in which an automotive sensor integration module 100according to an exemplary embodiment of the present invention isarranged may further include an upper-level control device 200 and acleaning control device 300.

Referring to FIG. 4, the vehicle may include the automotive sensorintegration module 100, the upper-level control device 200, and thecleaning control device 300.

The automotive sensor integration module 100 may synchronize pieces ofdetection data obtained from each sensor, and may provide synchronizeddata as sensing data S_data to the upper-level control device 200. Theautomotive sensor integration module 100 may generate reliability dataR_data on the basis of the detection data obtained from each sensor, andmay provide the generated reliability data R_data to the upper-levelcontrol device 200 and the cleaning control device 300.

The upper-level control device 200 may provide external environment dataEC_data to the automotive sensor integration module 100. The externalenvironment data EC_data may include at least one of weather, roadcondition, temperature, or humidity.

Although the automotive sensor integration module 100 according to anexemplary embodiment of the present invention is described as beingprovided with the external environment data EC_data from the upper-levelcontrol device 200, the automotive sensor integration module 100 may beprovided with the external environment data EC_data from a temperaturesensor, a humidity sensor, a rain sensor, and a navigation devicearranged in a vehicle.

The upper-level control device 200 may be a separate device forcontrolling the automotive sensor integration module 100, or a deviceincluded in an automated driving system or advanced driver assistancesystem (ADAS) to identify objects or control driving of a vehicle.

The upper-level control device 200 may identify an object on the basisof the sensing data S_data and the reliability data R_data provided fromthe automotive sensor integration module 100, and may control driving ofa vehicle according to an identification result. For example, theupper-level control device 200 may determine the sensing data S_data onthe basis of the reliability data R_data, and may identify an objectusing only the determined sensing data S_data. Therefore, objectidentification performance of the upper-level control device 200 may beimproved.

The cleaning control device 300 may determine whether each of outercover regions respectively corresponding to locations of the pluralityof sensors is contaminated on the basis of the reliability data R_dataprovided from the automotive sensor integration module 100. For example,when the cleaning control device 300 determines, on the basis of thereliability data R_data, that the sensing data S_data having lowreliability is output from the automotive sensor integration module 100,the cleaning control device 300 may determine that dirt or other foreignmatter has adhered to an outer cover of the automotive sensorintegration module 100.

When it is determined that dirt has adhered to the outer cover of theautomotive sensor integration module 100, the cleaning control device300 may provide a cleaning command to a cleaning device (not shown).

Here, the automotive sensor integration module 100, the upper-levelcontrol device 200, and the cleaning control device 300 may be connectedby vehicle network communication. A vehicle network communicationtechnology may include controller area network (CAN) communication,local interconnect network (LIN) communication, Flex-Ray® communication,Ethernet, and the like.

FIG. 5 is a diagram illustrating a configuration of an automotive sensorintegration module according to an exemplary embodiment of the presentinvention.

Referring to FIG. 5, the automotive sensor integration module 100according to an exemplary embodiment of the present invention mayinclude an optical camera 11, an infrared camera 12, a radar 13, a lidar14, an interface unit 20, and a signal processing unit 30. Here, theinterface unit 20 and the signal processing unit 30 may be implementedas hardware or software in the circuit board illustrated in FIG. 2.

The optical camera 11 may output information detected by medium of lightas first detection data C_s.

The infrared camera 12 may output information detected by medium ofinfrared light as second detection data IC_s.

The radar 13 may output information detected by medium ofelectromagnetic is waves as third detection data R_s.

The lidar 14 may output information detected by medium of laser light asfourth detection data L_s.

Here, the optical camera 11, the infrared camera 12, the radar 13, andthe lidar 14 may have different sensing (operation) periods. Forexample, the optical camera 11 and the infrared camera 12 may have asensing period of 30 Hz, the radar 13 may have a sensing period of 20Hz, and the lidar 14 may have a sensing period of 10 Hz.

Therefore, the optical camera 11 and the infrared camera 12 may outputthe first and second detection data C_s and IC_s every first time (33ms), the radar 13 may output the third detection data R_s every secondtime (50 ms), and the lidar 14 may output the fourth detection data L_severy third time (100 ms).

Furthermore, the detection data C_s, IC_s, R_s, and L_s respectivelyoutput from the optical camera 11, the infrared camera 12, the radar 13,and the lidar 14 may have different communication standards. Forexample, the first detection data C_s output from the optical camera 11may have a format used in low voltage differential signal (LVDS)communication. The second detection data IC_s output from the infraredcamera 12 may have a format used in gigabit multimedia serial link(GMSL) communication. The third and fourth detection data R_s and L_soutput from the radar 13 and the lidar 14 may have a format used inEthernet communication.

The interface unit 20 may convert the first to fourth detection dataC_s, IC_s, R_s, and L_s having different data formats into one presetdata format to provide converted data as conversion data C_data to thesignal processing unit 30. The interface unit 20 may convert the formatsof the first to fourth detection data C_s, IC_s, R_s, and L_s into adata format according is to a preset communication technology amongvehicle network communication technologies.

Here, the vehicle network communication technologies may includecontroller area network (CAN) communication, local interconnect network(LIN) communication, Flex-Ray® communication, Ethernet, and the like.For example, the interface unit 20 may convert the first to fourthdetection data C_s, IC_s, R_s, and L_s into data having a formataccording to Ethernet communication.

The signal processing unit 30 may receive, as the conversion dataC_data, the first to fourth detection data C_s, IC_s, R_s, and L_sconverted by the interface unit 20 and having the same format. Thesignal processing unit 30 may output the first to fourth detection dataC_s, IC_s, R_s, and L_s included in the conversion data C_data providedfrom the interface unit 20 to the upper-level control device 200 assensing data S_data in synchronization with a preset timing.

For example, the signal processing unit 30 may output the first tofourth detection data C_s, IC_s, R_s, and L_s as the sensing data S_dataat the same timing on the basis of an input timing of one of the firstto fourth detection data C_s, IC_s, R_s, and L_s. In more detail, thesignal processing unit 30 may receive and store the first-to-fourthdetection data C_s, IC_s, R_s, and L_s, and may output the storedfirst-to-fourth detection data C_s, IC_s, R_s, and L_s as the sensingdata S_data after a preset time has passed after the third detectiondata R_s was input to the signal processing unit 30.

Here, the sensing data S_data may include the first-to-fourth detectiondata C_s, IC_s, R_s, and L_s obtained from the optical camera 11, theinfrared camera 12, the radar 13, and the lidar 14.

Furthermore, the signal processing unit 30 may generate the reliabilitydata R_data on the basis of the external environment data EC_data andthe conversion data C_data, and may provide the generated reliabilitydata R_data to the upper-level control device 200 and the cleaningcontrol device 300.

For example, the signal processing unit 30 may determine, on the basisof the conversion data C_data and the external environment data, thereliability of each of the first to fourth detection data C_s, IC_s,R_s, and L_s output from the optical camera 11, the infrared camera 12,the radar 13, and the lidar 14, and may output a determination result asthe reliability data R_data.

FIG. 6 is a diagram illustrating a configuration of the signalprocessing unit of FIG. 5.

Referring to FIG. 6, the signal processing unit 30 may include a datatransmitting/receiving unit 31, an output synchronization unit 32, and adata reliability determination unit 33.

The data transmitting/receiving unit 31 may include a wired/wirelesscommunication module for transmitting/receiving data to/from theinterface unit 20, the upper-level control device 200, and the cleaningcontrol device 300.

The data transmitting/receiving unit 31 may transmit, to the upper-levelcontrol device 200, the sensing data S_data received from the outputsynchronization unit 32. The data transmitting/receiving unit 31 maytransmit, to the upper-level control device 200 and the cleaning controldevice 300, the reliability data R_data received from the datareliability determination unit 33.

The data transmitting/receiving unit 31 may transmit, to the datareliability determination unit 33, the external environment data EC_datareceived from the upper-level control device 200. The datatransmitting/receiving unit 31 may transmit, to the outputsynchronization unit 32 and the data reliability determination unit 33,the conversion data C_data received from the interface unit 20.

The output synchronization unit 32 may generate the sensing data S_databy synchronizing the conversion data C_data provided from the datatransmitting/receiving unit 31, and may provide the generated sensingdata to the data transmitting/receiving unit 31. For example, the outputsynchronization unit 32 may synchronize the first-to-fourth detectiondata C_s, IC_s, R_s, and L_s on the basis of any one of thefirst-to-fourth detection data C_s, IC_s, R_s, and L_s included in theconversion data C_data to provide the synchronized data to the datatransmitting/receiving unit 31 as the sensing data S_data.

In more detail, the output synchronization unit 32 may store each of thefirst-to-fourth detection data C_s, IC_s, R_s, and L_s included in theconversion data C_data, and may output the stored first-to-fourthdetection data C_s, IC_s, R_s, and L_s as the sensing data S_data when apreset time has passed after input of any one of the first-to-fourthdetection data C_s, IC_s, R_s, and L_s.

The data reliability determination unit 33 may generate the reliabilitydata R_data on the basis of the conversion data C_data and the externalenvironment data EC_data provided from the data transmitting/receivingunit 31, and may provide the generated reliability data R_data to thedata transmitting/receiving unit 31.

Here, the conversion data C_data includes the first-to-fourth detectiondata C_s, IC_s, R_s, and L_s obtained from the optical camera 11, theinfrared camera 12, the radar 13, and the lidar 14, and the datareliability determination unit 33 generates the reliability data R_dataon the basis of each of the first to fourth detection data C_s, IC_s,R_s, and L_s and the is external environment data EC_data, and thus, thereliability data R_data may include the reliability of each of thefirst-to-fourth detection data C_s, IC_s, R_s, and L_s output from eachsensor.

For example, in cases when dirt or other foreign matter may easilyadhere to the outer cover of the automotive sensor integration module100 on the basis of the external environment data EC_data includingweather, temperature, humidity, and road conditions, the datareliability determination unit 33 may generate the reliability dataR_data indicating low reliability for each of the first-to-fourthdetection data C_s, IC_s, R_s, and L_s.

Furthermore, in cases when dirt or other foreign matter may not easilyadhere to the outer cover of the automotive sensor integration module100 on the basis of the external environment data EC_data, the datareliability determination unit 33 may generate the reliability dataR_data indicating high reliability for each of the first-to-fourthdetection data C_s, IC_s, R_s, and L_s.

Here, dirt or other foreign matter may more easily adhere to the outercover of the automotive sensor integration module 100 in a situation inwhich it rains or snows; the temperature is low enough to produce frost;or the humidity is high, than in a situation in which it does not rainor snow; the temperature is high enough such that frost is notgenerated; or the humidity is low.

FIG. 7 is a diagram illustrating a configuration of the data reliabilitydetermination unit of FIG. 6.

As illustrated in FIG. 7, the data reliability determination unit 33 mayinclude an optical camera reliability determination unit 33-1, aninfrared camera reliability determination unit 33-2, a radar reliabilitydetermination unit 33-3, and a lidar reliability determination unit33-4.

As described above, the data reliability determination unit 33 maydetermine, on the basis of the external environment data EC_data, thereliability of each of the first-to-fourth detection data C_s, IC_s,R_s, and L_s included in the conversion data C_data, and may output adetermination data as the reliability data R_data.

The optical camera reliability determination unit 33-1 may generate anoptical camera reliability value RC_s on the basis of the firstdetection data C_s and the external environment data EC_data, and mayoutput the generated optical camera reliability value RC_s as thereliability data R_data.

For example, the optical camera reliability determination unit 33-1 mayincrease the optical camera reliability value RC_s as the number ofoccurrences of data which enables color discrimination from the firstdetection data C_s output from the optical camera 11 increases during apreset time.

When a data value difference occurs between the previous first detectiondata C_s and the current first detection data C_s, the optical camerareliability determination unit 33-1 may increase the optical camerareliability value RC_s. On the basis of the external environment dataEC_data, the optical camera reliability determination unit 33-1 mayfurther decrease the optical camera reliability value RC_s when it rainsor snows than when it does not rain or snow, and may further decreasethe optical camera reliability value RC_s when a vehicle travels on anunpaved road than when a vehicle travels on a paved road.

In more detail, the optical camera reliability determination unit 33-1may calculate the optical camera reliability value RC_s using theformula w1*R1+w2*R2+w3*R3+w4*R4. Here, w1, w2, w3, and w4 may be weightvalues, and R1 may be a value which is increases or decreases accordingto the number of occurrences of data which enables color discriminationfrom the first detection data C_s output from the optical camera 11during a preset time. R2 may be a value which increases or decreasesaccording to the data value difference between the previous firstdetection data C_s and the current first detection data C_s. R3 may be avalue which increases or decreases according to rainy or snowy weather,temperature, or humidity from the external environment data EC_data. R4may be a value which increases or decreases according to a condition ofa road on which a vehicle travels from the external environment dataEC_data.

The infrared camera reliability determination unit 33-2 may generate aninfrared camera reliability value RIC_s on the basis of the seconddetection data IC_s and the external environment data EC_data, and mayoutput the generated infrared camera reliability value RIC_s as thereliability data R_data.

For example, the infrared camera reliability determination unit 33-2 mayincrease the infrared camera reliability value RIC_s as the number ofoccurrences of data which enables color discrimination from the seconddetection data IC_s output from the infrared camera 12 increases duringa preset time. When there occurs a data value difference between theprevious second detection data IC_s and the current second detectiondata IC_s, the infrared camera reliability determination unit 33-2 mayincrease the infrared camera reliability value RIC_s.

On the basis of the external environment data EC_data, the infraredcamera reliability determination unit 33-2 may further decrease theinfrared camera reliability value RIC_s when it rains or snows than whenit does not rain or snow, and may further decrease the infrared camerareliability value RIC_s when a vehicle travels on an unpaved road thanwhen a vehicle travels on a paved road.

In more detail, the infrared camera reliability determination unit 33-2may calculate the infrared camera reliability value RIC_s using theformula w1*R1+w2*R2+w3*R3+w4*R4. Here, w1, w2, w3, and w4 may be weightvalues, and R1 may be a value which increases or decreases according tothe number of occurrences of data which enables color discriminationfrom the second detection data IC_s output from the infrared camera 12during a preset time. R2 may be a value which increases or decreasesaccording to the data value difference between the previous seconddetection data IC_s and the current second detection data IC_s. R3 maybe a value which increases or decreases according to rainy or snowyweather, temperature, or humidity from the external environment dataEC_data. R4 may be a value which increases or decreases according to acondition of a road on which a vehicle travels from the externalenvironment data EC_data.

The radar reliability determination unit 33-3 may generate a radarreliability value RR_s on the basis of the third detection data R_s andthe external environment data EC_data, and may output the generatedradar reliability value RR_s as the reliability data R_data.

For example, the radar reliability determination unit 33-3 may increasethe radar reliability value RR_s as the number of occurrences of datawhich enables distance determination from the third detection data R_soutput from the radar 13 increases during a preset time. When thereoccurs a data value difference between the previous third detection dataR_s and the current third detection data R_s, the radar reliabilitydetermination unit 33-3 may increase the radar reliability value RR_s.

On the basis of the external environment data EC_data, the radarreliability determination unit 33-3 may further decrease the radarreliability value RR_s when it rains or snows than when it does not rainor snow, and may further decrease the radar reliability value RR_s whena vehicle travels on an unpaved road than when a vehicle travels on apaved road.

In more detail, the radar reliability determination unit 33-3 maycalculate the radar reliability value RR_s using the formulaw1*R1+w2*R2+w3*R3+w4*R4. Here, w1, w2, w3, and w4 may be weight values,and R1 may be a value which increases or decreases according to thenumber of occurrences of data which enables distance determination fromthe third detection data R_s output from the radar 13 during a presettime. R2 may be a value which increases or decreases according to thedata value difference between the previous third detection data R_s andthe current third detection data R_s. R3 may be a value which increasesor decreases according to rainy or snowy weather, temperature, orhumidity from the external environment data EC_data. R4 may be a valuewhich increases or decreases according to a condition of a road on whicha vehicle travels from the external environment data EC_data.

The lidar reliability determination unit 33-4 may generate a lidarreliability value RL_s on the basis of the fourth detection data L_s andthe external environment data EC_data, and may output the generatedlidar reliability value RL_s as the reliability data R_data.

For example, the lidar reliability determination unit 33-4 may increasethe lidar reliability value RL_s as the number of occurrences of datawhich enables distance determination from the fourth detection data L_soutput from the lidar 14 increases during a preset time. When thereoccurs a data value difference between the previous fourth detectiondata L_s and the current fourth detection data L_s, the lidarreliability determination unit 33-4 may increase the lidar reliabilityvalue RL_s.

On the basis of the external environment data EC_data, the lidarreliability determination unit 33-4 may further decrease the lidarreliability value RL_s when it rains or snows than when it does not rainor snow, and may further decrease the lidar reliability value RL_s whena vehicle travels on an unpaved road than when a vehicle travels on apaved road.

In more detail, the lidar reliability determination unit 33-4 maycalculate the lidar reliability value RL_s using the formulaw1*R1+w2*R2+w3*R3+w4*R4. Here, w1, w2, w3, and w4 may be weight values,and R1 may be a value which increases or decreases according to thenumber of occurrences of data which enables distance determination fromthe fourth detection data L_s output from the lidar 14 during a presettime. R2 may be a value which increases or decreases according to thedata value difference between the previous fourth detection data L_s andthe current fourth detection data L_s. R3 may be a value which increasesor decreases according to rainy or snowy weather, temperature, orhumidity from the external environment data EC_data. R4 may be a valuewhich increases or decreases according to a condition of a road on whicha vehicle travels from the external environment data EC_data.

As described above, the automotive sensor integration module 100according to the present invention may detect the reliability of each ofthe detection data C_s, IC_s, R_s, and L_s respectively output from theoptical camera 11, the infrared camera 12, the radar 13, and the lidar14 and may provide the reliability to the upper-level control device 200for identifying an object, and thus the object identificationperformance of an automated driving system or ADAS system in which theautomotive sensor integration module 100 according to the presentinvention is applied may be improved.

Furthermore, the automotive sensor integration module 100 according tothe present invention may detect the reliability of each of thedetection data C_s, IC_s, R_s, and L_s respectively output from theoptical camera 11, the infrared camera 12, the radar 13, and the lidar14 and may provide the reliability to the cleaning control device 300 sothat the reliability may be used in cleaning the outer cover of theautomotive sensor integration module 100, and thus the reliability ofdetection data of sensors may be improved. Therefore, the objectdetermination performance of an automated driving system or ADAS systemin which the automotive sensor integration module 100 according to thepresent invention is applied may be improved.

The automotive sensor integration module according to an exemplaryembodiment of the present invention has improved performance ofdetecting objects outside a vehicle since a plurality of sensors aresynchronously operated.

Furthermore, the automotive sensor integration module according to anexemplary embodiment of the present invention has improved performanceof detecting objects outside a vehicle since the reliability ofdetection data of each of a plurality of sensors is determined.

Although exemplary embodiments of the present disclosure have been shownand described hereinabove, the present disclosure is not limited tospecific exemplary embodiments described above, but may be variousmodified by those skilled in the art to which the present disclosurepertains without departing from the scope and spirit of the disclosureas disclosed in the accompanying claims. In addition, such modificationsshould also be understood to fall within the scope and spirit of thepresent disclosure.

What is claimed is:
 1. An automotive sensor integration modulecomprising: a plurality of sensors differing from each other in at leastone of a sensing period or an output data format; and a signal processorconfigured to: simultaneously output, as sensing data, pieces ofdetection data respectively output from the plurality of sensors on thebasis of the sensing period of any one of the plurality of sensors;calculate a reliability value of each of the pieces of detection data onthe basis of the pieces of detection data and external environment data;and output the reliability value as reliability data.
 2. The automotivesensor integration module of claim 1, wherein the signal processorreceives and stores the pieces of detection data, and simultaneouslyoutputs the stored pieces of detection data on the basis of the sensingperiod of any one of the plurality of sensors.
 3. The automotive sensorintegration module of claim 1, wherein the signal processor increases ordecreases the reliability values of the pieces of detection dataaccording to the number of occurrences of data which enables at leastone of color discrimination or distance determination from the pieces ofdetection data.
 4. The automotive sensor integration module of claim 3,wherein the signal processor increases the reliability values of thepieces of detection data as the number of occurrences of data whichenables at least one of color discrimination or distance determinationfrom the pieces of detection data increases.
 5. The automotive sensorintegration module of claim 1, wherein the signal processor increases ordecreases the reliability values of the pieces of detection dataaccording to whether a data value difference occurs between current dataand previous data of the pieces of detection data.
 6. The automotivesensor integration module of claim 5, wherein the signal processorincreases the reliability values of the pieces of detection data whenthe data value difference occurs between the current data and theprevious data of the pieces of detection data.
 7. The automotive sensorintegration module of claim 1, wherein the signal processor increases ordecreases the reliability values of the pieces of detection dataaccording to whether it rains or snows or a road is paved on the basisof the external environment data.
 8. The automotive sensor integrationmodule of claim 7, wherein the signal processor decreases thereliability values of the pieces of detection data to a greater degreewhen it rains or snows than when it does not rain or snow.
 9. Theautomotive sensor integration module of claim 8, wherein the signalprocessor decreases the reliability values of the pieces of detectiondata to a greater degree when a vehicle travels on an unpaved road thanwhen the vehicle travels on a paved road.
 10. The automotive sensorintegration module of claim 1, wherein the signal processor increases ordecreases the reliability values of the pieces of detection data on thebasis of at least one of: the number of occurrences of data whichenables at least one of color discrimination or distance determinationfrom the pieces of detection data; and whether there occurs a data valuedifference between current data and previous data of the pieces ofdetection data, weather, or a road pavement state.
 11. An automotivesensor integration module comprising: a plurality of sensors differingfrom each other in at least one of a sensing period or an output dataformat; an output synchronization unit configured to simultaneouslyoutput, as sensing data, pieces of detection data respectively outputfrom the plurality of sensors on the basis of the sensing period of anyone of the plurality of sensors; and a data reliability determinationunit configured to calculate a reliability value of each of the piecesof detection data on the basis of the pieces of detection data andexternal environment data, and output the reliability value asreliability data.
 12. The automotive sensor integration module of claim11, further comprising a data transmitting/receiving unit configured to:transfer the pieces of detection data output from the plurality ofsensors to the output synchronization unit and the data reliabilitydetermination unit; transfer the sensing data output from the outputsynchronization unit to an upper-level control device; transfer thereliability data output from the data reliability determination unit tothe upper-level control device and a cleaning control device; andtransfer the external environment data provided from the upper-levelcontrol device or an external device to the data reliabilitydetermination unit.
 13. The automotive sensor integration module ofclaim 11, wherein the output synchronization unit receives and storesthe pieces of detection data, and simultaneously outputs the storedpieces of detection data on the basis of the sensing period of any oneof the plurality of sensors.
 14. The automotive sensor integrationmodule of claim 11, wherein the plurality of sensors comprise at leastone of an optical camera, an infrared camera, a radar, or a lidar. 15.The automotive sensor integration module of claim 14, wherein the datareliability determination unit comprises at least one of: an opticalcamera reliability determination unit configured to calculate an opticalcamera reliability value on the basis of first detection data outputfrom the optical camera and the external environment data; an infraredcamera reliability determination unit configured to calculate aninfrared camera reliability value on the basis of second detection dataoutput from the infrared camera and the external environment data; aradar reliability determination unit configured to calculate a radarreliability value on the basis of third detection data output from theradar and the external environment data; and a lidar reliabilitydetermination unit configured to calculate a lidar reliability value onthe basis of fourth detection data output from the lidar and theexternal environment data.
 16. The automotive sensor integration moduleof claim 15, wherein: the optical camera reliability determination unitcalculates the optical camera reliability value according to at leastone of: the number of occurrences of data which enables colordiscrimination from the first detection data; and whether there occurs adata value difference between previous data and current data of thefirst detection data, weather, and a road pavement state; and theoptical camera reliability determination unit outputs a calculated valueas the reliability data.
 17. The automotive sensor integration module ofclaim 15, wherein: the infrared camera reliability determination unitcalculates the infrared camera reliability value according to at leastone of: the number of occurrences of data which enables colordiscrimination from the second detection data; and whether there occursa data value difference between previous data and current data of thesecond detection data, weather, and a road pavement state; and theinfrared camera reliability determination unit outputs a calculatedvalue as the reliability data.
 18. The automotive sensor integrationmodule of claim 15, wherein: the radar reliability determination unitcalculates the radar reliability value according to at least one of: thenumber of occurrences of data which enables distance determination fromthe third detection data; and whether there occurs a data valuedifference between previous data and current data of the third detectiondata, weather, and a road pavement state; and the radar reliabilitydetermination unit outputs a calculated value as the reliability data.19. The automotive sensor integration module of claim 15, wherein: thelidar reliability determination unit calculates the lidar reliabilityvalue according to at least one of: the number of occurrences of datawhich enables distance determination from the fourth detection data; andwhether there occurs a data value difference between previous data andcurrent data of the fourth detection data, weather, and a road pavementstate; and the lidar reliability determination unit outputs a calculatedvalue as the reliability data.